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Space/Time: Methods in Geospatial Computing for Mapping the Past

A workgroup organized by Stuart Dunn, AHeSSC, King's College London at the e-Science Institute, Edinburgh (23 - 24 July 2007). This workgroup followed the e-Science in the arts and humanities theme lecture on Space and Time.

(pdf) (html) Programme
(pdf) Participants
(pdf) (html) Workgroup report
(html) Workgroup wiki
(html) Mapping the Past online discussion group
(html) AHeSSC Briefing Paper on Geospatial Resources

Many excellent case studies exist of application of geospatial technologies in the archaeological and historical domains, and particular aspects of the subject have been examined in cross-regional and cross-methodological ways. These have been stimulated by - and stimulate - rapid technological change, and a deeper embedding of that technology in research, as scholars from across the humanities become progressively more aware of the immense enabling power offered by approaching, managing and analyzing their resources geospatially. As this agenda moves beyond the traditional 'magic circle' of so-called 'Spatially Aware Professionals' to production-level services and methods in the wider humanities communities, we feel that the time has come for a domain-wide overview of the methodologies; how their different aspects are defined; and how, once defined, those aspects can inform and provoke research-led development in one another. Over two days, an international and interdisciplinary group of experts came together to address this. The workshop organizers identified three high-level aspects:


Ubiquitous variation in data quality and quantity from both temporal and spatial perspectives create serious difficulties in representing information in a consistent way. Issues that were discussed included: How can such variations in precision and accuracy be made transparent? What are the dangers and pitfalls of inter-scale analyses and how can they be avoided? What are the relevant pros and cons of showing time and space as totalities as opposed to discrete units? Does GIS provide us with new tools that permit us to go beyond traditional 2-dimensional cartographic solutions to these problems? Should interpolated data be represented differently?


Mapping the past often requires the use of multiple datasets, often structured in different ways and for entirely different purposes. Integrating such data requires sophisticated approaches in order not to derive false inferences. Issues discussed include: How can spatial and temporal data most clearly and easily be provenanced? What methods can provide overviews of similarity/disparity between multiple datasets? What are the benefits and disadvantages of layered vs. unified approaches? What is the ontological status of data derived from mixed sources?

Standard and metadata

Published maps generally represent only a ‘final analysis’ and obscure the series of decisions which have led to their instantiation. In order to enable future researchers to understand the conditions which led to their creation these decisions must also be documented. Issues considered include: What metadata is necessary and/or sufficient? What standards are needed for using and managing geospatial data? How can we deal with ‘big data’? Should ‘early variants’ be stored? If so, how? How can GIS systems maintain links to their epistemic source? Should informational absence be recorded?

Discussion of these issues continues at the Mapping the Past group at the Digital Arts & Humanities community site.

AHDS Methods Taxonomy Terms

This item has been catalogued using a discipline and methods taxonomy. Learn more here.


  • Archaeology


  • Data Analysis - Predictive spatial modelling
  • Data Structuring and enhancement - Coding/standardisation
  • Data Structuring and enhancement - Geo-referencing/projection
  • Data Structuring and enhancement - Graphical rendering
  • Data Structuring and enhancement - Image enhancement
  • Data Structuring and enhancement - Image restoration and rectification
  • Data Capture - Geophysical survey
  • Data Capture - Digital remote sensing
  • Data Capture - GPS/total station surveys
  • Data Capture - Usage of existing digital data